Design of a Logistics Network in an Organisation for Optimising Logistics Cost and Inventory Using RSM and Genetic Algorithm

Abstract:

The competitive environment of global markets has forced many manufacturers to select the most appropriate logistics for the optimisation of total logistics costs, time and inventory. Cost and time are the two important factors in the competitive market that are often not addressed comprehensively by the researchers. In this study, the genetic algorithms (GAs) and the fuzzy logic techniques are used for optimising a novel mathematical model of the logistics network. The objective of the proposed model is to minimise the costs of production, distribution, holding and backorder. In addition to the optimization of logistics costs, the model can also determine the economic production quantity (EPQ), and with help of the GAs and the Fuzzy logic solver with probability parameters and various dimensions for validation of the studied model in real-life situations, and we compared the outputs to demonstrate the performance of the two optimization techniques . Using Genetic Algorithm and fuzzy logic, the optimized value of the logistics cost, and volume of the logistics network were obtained.

• Periodical: Applied Mechanics and Materials (Volumes 592-594)
• Pages: 2601-2607
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.592-594.2601
• Online since: July 2014
• Authors: Venkatesh Rajendran*, S.R. Devadasan, S. Kannan
• Keywords: Fuzzy Logic, Genetic Algorithm (GA), Logistics Network, Optimization, RSM

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